Senior Fullstack Data Scientist w Polska

· 8+ years of experience in Data Science/AI engineering

· At least 4+ years of experience in production-ready Python AI-related code development.

· At least 2+ years of experience in production-ready LLM-related code development, preferably based on the Retrieval-Augmented Generation (RAG) concept.

· Strong analytical and problem-solving skills with the ability to optimize AI solutions for diverse applications.

· Strong knowledge and experience in Generative AI, including LLMs, chatbots, AI agents, and RAG mechanisms.

· Deep understanding of LLM evaluators, validators, and guardrails.

· Hands‑on experience with one or more GenAI frameworks: LangChain, LlamaIndex, LangGraph, or similar orchestration stacks.

· Hands‑on experience designing or operating MCP servers/clients for LLM agents

· Strong Python skills, including production‑grade code, packaging, and testing for data/ML services

· Solid understanding of ML/AI concepts: types of algorithms, machine learning frameworks, model efficiency metrics, model lifecycle, AI architectures.

· Proven ability to collaborate effectively across technical and non-technical teams.

· Familiarity with cloud environments such as Azure (preferred), GCP, or AWS, including AI-related managed services.

· Familiarity with CI/CD, testing, and containerized deployments.

· Excellent communication skills in English, with the ability to convey complex technical concepts to various audiences.

Nice-to-Have Skills & Knowledge:

· Experience in designing and programming ML algorithms and data processing pipelines using Python.

· Good understanding of CI/CD and DevOps concepts, with experience working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps).

· Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes.

· Experience with agentic AI development frameworks (e.g., BMAD, multi‑agent orchestration, spec‑driven AI workflows).

• Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites.
• “Office as an option” model. You can choose to work remotely or in the office.
• Workation. Enjoy working from inspiring locations in line with our workation policy.
• Great Place to Work® certified employer.
• Flexibility regarding working hours and your preferred form of contract.
• Comprehensive online onboarding program with a “Buddy” from day 1.
• Cooperation with top-tier engineers and experts.
• Unlimited access to the Udemy learning platform from day 1.
• Certificate training programs. Lingarians earn 500+ technology certificates yearly.
• Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
• Grow as we grow as a company. 76% of our managers are internal promotions.
• A diverse, inclusive, and values-driven community.
• Autonomy to choose the way you work. We trust your ideas.
• Create our community together. Refer your friends to receive bonuses.
• Activities to support your well-being and health.
• Plenty of opportunities to donate to charities and support the environment.
• Modern office equipment. Purchased for you or available to borrow, depending on your location.

,[Lead discovery and solution design for GenAI use cases, translating business problems into concrete architectures (LLM decision, RAGs, fine tuning, agents, guardrails), Build end to end GenAI applications: data ingestion, retrieval layer, orchestration (e.g. LangChain/LlamaIndex/LangGraph), API/backend, and simple UI where needed., Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness., Perform model selection, prompting strategies, and fine tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including evaluation and A/B testing., Implement safety, compliance, and governance controls (input/output filters, PII handling, audit logs, human in the loop review where required)., Collaborate with data engineers, product owners, and full stack developers on scalable architectures, SLAs, and integration with existing enterprise systems, Gather technical requirements and estimate planned work., Mentor other data scientists/engineers in GenAI patterns, code quality, and best practices; contribute to internal libraries, templates, and reusable components., Stay current with GenAI landscape (new open and hosted models, agentic frameworks, evaluation techniques) and perform targeted PoCs to validate them.] Requirements: Python, Data science, LLM, AI